Knowledge graphs are widely used tools in the field of reasoning, where reasoning is
facilitated through link prediction within the knowledge graph. However, traditional methods …

For any positive integer n, we use [n] for the set {1,…, n}. For any integers a 1,…, an≥ 2 and
k≥ 1, the generalized Hamming graph H a 1,…, ank is the graph with vertex set [a 1]×⋯×[an] …

Feature selection plays a vital role in machine learning by removing the features which are
irrelevant for the learning task in high dimensional datasets. Selecting the relevant features …

Srivastava et al. propose a parallel framework to optimize Bayesian network learning in the
SC20 article entitled “A Parallel Framework for Constraint-Based Bayesian Network …

The thesis studies the how to efficiently and effectively learn Markov blankets from data. The
thesis also studies some of the properties of Markov blankets, so that their quality can be …